Ryota Kobayashi

发表

Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron

Shigeru Shinomoto, Ryota Kobayashi, Yasuhiro Tsubo, 2011, NIPS.

TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics pdf

Renaud Lambiotte, Ryota Kobayashi, R. Lambiotte, 2016, ICWSM.

Effective and Stable Neuron Model Optimization Based on Aggregated CMA-ES

Han Xu, Ryota Kobayashi, Takahiro Shinozaki, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model

Katsunori Kitano, Ryota Kobayashi, 2013, Journal of Computational Neuroscience.

A fast-computational spiking neuron model adaptable to any cortical neuron

Shigeru Shinomoto, Ryota Kobayashi, Yasuhiro Tshubo, 2009, BMC Neuroscience.

Optimal decoding and information transmission in Hodgkin-Huxley neurons under metabolic cost constraints

Ryota Kobayashi, Lubomir Kostal, L. Kostal, 2015, Biosyst..

Estimation of the synaptic input firing rates and characterization of the stimulation effects in an auditory neuron

Ryota Kobayashi, Petr Lánský, Jufang He, 2015, Front. Comput. Neurosci..

Dynamics on global brain networks at the neuronal resolution

Ryota Kobayashi, Masanori Shimono, 2015, BMC Neuroscience.

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Karl Aberer, Philippe Cudré-Mauroux, Ryota Kobayashi, 2017, WWW.

A Survey of Results on Large-Scale Brain Simulation

Ryota Kobayashi, 2015 .

Simultaneous Local Adaptation for Different Local Properties

Hiroyuki Sato, Ryota Kobayashi, Keiki Takadama, 2019, IES.

Interactive Projection System That Always Presents Information within User’s View

Ryota Kobayashi, Jun-ichi Imai, Kazuya Jinjo, 2016, 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS).

A method for estimating of synaptic connectivity from spike data of multiple neurons

Katsunori Kitano, Ryota Kobayashi, K. Kitano, 2016 .

Excitation system by contactless power transfer system with the primary series capacitor method

Yasuyoshi Kaneko, Ryota Kobayashi, Shigeru Abe, 2014, 2014 International Power Electronics Conference (IPEC-Hiroshima 2014 - ECCE ASIA).

Estimation of Time-Dependent Input from Neuronal Membrane Potential

Shigeru Shinomoto, Ryota Kobayashi, Petr Lánský, 2011, Neural Computation.

Made-to-Order Spiking Neuron Model Equipped with a Multi-Timescale Adaptive Threshold

Shigeru Shinomoto, Ryota Kobayashi, Yasuhiro Tsubo, 2009, Front. Comput. Neurosci..

Impact of slow K+ currents on spike generation can be described by an adaptive threshold model

Katsunori Kitano, Ryota Kobayashi, K. Kitano, 2016, Journal of Computational Neuroscience.

Reconstructing neuronal circuitry from parallel spike trains

Katsunori Kitano, Markus Diesmann, Barry J. Richmond, 2019, Nature Communications.

Conductance estimation of a conductance-based neuron model by the differential evolution algorithm

Katsunori Kitano, Ryota Kobayashi, Mao Suzuka, 2013, BMC Neuroscience.

Estimating synaptic connections from multiple spike trains based on a coupled escape rate model

Katsunori Kitano, Ryota Kobayashi, 2013, BMC Neuroscience.

How slow K+ currents impact on spike generation mechanism?

Katsunori Kitano, Ryota Kobayashi, 2015, BMC Neuroscience.

A benchmark test for a quantitative assessment of simple neuron models

Wulfram Gerstner, Richard Naud, Ryota Kobayashi, 2008, Journal of Neuroscience Methods.

Input-output relationship in social communications characterized by spike train analysis

Taro Takaguchi, Renaud Lambiotte, Ryota Kobayashi, 2016, Physical review. E.

Reconstructing neuronal circuitry from parallel spike trains

Katsunori Kitano, Barry J. Richmond, Shigeru Shinomoto, 2018, Nature Communications.

A single spike deteriorates synaptic conductance estimation

Hisao Nishijo, Ryota Kobayashi, Petr Lánský, 2017, Biosyst..

Predicting spike times from subthreshold dynamics of a neuron

Shigeru Shinomoto, Ryota Kobayashi, 2006, NIPS.

Population coding is essential for rapid information processing in the moth antennal lobe

Katsunori Kitano, Ryohei Kanzaki, Ryota Kobayashi, 2013, Brain Research.